Visitor identification
Persistent identification when IP changes
Understand traffic quality and visitor anonymity levels and protect your revenue from hidden abuse
Shieldlabs evaluates traffic quality and visitor anonymity levels even under deep masking, analyzes abuse patterns, and provides an explainable risk score for each visit
Anonymity detection
Detect VPN, proxy, and anti-detect browser
Abuse analysis
Detect multi-accounting patterns
Explainable Risk Score
Clear reasons and risk level
False positive reduction
Fewer errors without losing conversion
Anonymous traffic impacts business
The scale often remains unnoticed
Wasted Conversion Opportunities
Free access is used, but people don't buy.
Bonus & Reward Abuse
Giveaways and bonuses go to non-real users.
Drained Marketing Budget
Marketing budget is spent on fake activity.
Legitimate User Churn
Real users leave due to extra checks and blocks.
High Operational Costs
Traffic assessment requires expensive enterprise solutions or specialists.
Distorted Analytics Data
Metrics are distorted — conversion, CAC, and LTV are calculated on false data.
Key Features
Visitor Identification
Identification of a visitor even when IP address, cookies, or account change.
High-Precision Network Analysis
Detection of IP address, provider, network and connection type, geolocation, and reputation with up to 99% accuracy.
Deep Intelligence
Cross-layer analysis of device, operating system, browser, and network signals to detect inconsistencies and signs of masking.
Explainable Risk Score
Assignment of a Risk Score to traffic and each visitor, indicating risk level, scoring reasons, and contributing factors.
Abuse Patterns
Correlation of related entities and detection of abuse based on ready-made patterns with assessment of their scale and risk level.
API and Webhooks
Transmission of detailed data and Risk Score via API and Webhooks for automation of rules and protection scenarios.
Enterprise-Grade without Enterprise Cost
Providing enterprise-level analysis with fast integration and transparent pricing.
What Shieldlabs detects
Shieldlabs detects anonymization methods, masking techniques, and abuse activity across device, operating system, browser, and network levels.
VPN
Detection of connections through VPN providers and rotating IP infrastructure.
Proxy
Detection of connections through proxy servers of various types.
TOR
Detection of connections through the TOR network.
Privacy Relay
Detection of connections through Privacy Relay services.
Anti-detect browsers
Detection of browsers designed for masking.
Data center and hosting infrastructure
Detection of connections originating from data centers, cloud providers, and VPS infrastructure.
Environment spoofing
Detection of attempts to hide or alter real device, OS, and browser parameters.
Abuse activity
Detection of abuse activity indicating multi-accounting, account sharing, and signs of account compromise.
Use Cases
Where Shieldlabs helps identify risk and prevent abuse
Account Registrations
Detect when one person creates multiple accounts to commit multi-account abuse. Prevent fake registrations and maintain a real, trustworthy user base.
Free Trial and Freemium
Detect when users create new accounts to commit free trial abuse. Prevent repeated access and protect conversion to paid plans.
Subscriptions and Paid Access
Detect activity associated with subscription abuse and unauthorized access. Protect recurring revenue and maintain subscription integrity.
Account Sharing
Detect when one account is used by multiple users, indicating account sharing abuse. Prevent revenue loss and protect subscription value.
Plan and Usage Limit Bypass
Detect when users create accounts to bypass plan limits and commit usage abuse. Prevent abuse of product access and ensure fair usage.
Ban and Restriction Evasion
Detect when blocked users return under a new identity to evade enforcement. Prevent ban evasion and ensure platform integrity.
Referral Programs
Detect when users create accounts to commit referral abuse. Prevent referral fraud and protect acquisition efficiency.
Bonuses and Promotional Campaigns
Detect when users claim bonuses and promotional offers to commit bonus or incentive abuse. Prevent promotional abuse and protect marketing ROI.
Giveaways and Contests
Detect when users attempt to claim giveaway rewards and contest prizes to commit giveaway abuse. Prevent giveaway fraud and protect campaign fairness.
Traffic Quality and Acquisition
Detect anonymous visitors and traffic abuse. Prevent wasted acquisition spend and improve traffic quality.
Cryptocurrency / Web3
Detect sybil abuse and farming activity in crypto airdrops and reward campaigns. Protect fair reward distribution and prevent farming abuse.
Voting and Ratings
Detect when users submit multiple votes, indicating voting fraud. Prevent manipulation and ensure trustworthy outcomes.
Surveys and Data Collection
Detect when users submit multiple responses to commit survey fraud. Prevent data manipulation and protect analytics integrity.
How it works
From integration to explainable risk assessment and action
Fast Integration
Add a few lines of JavaScript and start analysis within minutes. Shieldlabs automatically identifies the visitor and collects signals.
Risk Score Calculation
Detection of anonymity indicators and assignment of a numerical Risk Score to each visitor and traffic source. The more inconsistencies and anonymity signals detected, the higher the final risk level.
Abuse Pattern Detection
The system correlates signals within a visit and over time, identifying abuse patterns. This helps uncover related entities and understand the overall level of risk.
Explainable Details & Action
Risk Score and scoring reasons are available in the dashboard or via API and Webhooks. Use the data to build your own rules, automate workflows, and make informed decisions.
How it works
From integration to explainable risk assessment and action
Fast Integration
Add a few lines of JavaScript and start analysis within minutes. Shieldlabs automatically identifies the visitor and collects signals.
Risk Score Calculation
Detection of anonymity indicators and assignment of a numerical Risk Score to each visitor and traffic source. The more inconsistencies and anonymity signals detected, the higher the final risk level.
Abuse Pattern Detection
The system correlates signals within a visit and over time, identifying abuse patterns. This helps uncover related entities and understand the overall level of risk.
Explainable Details & Action
Risk Score and scoring reasons are available in the dashboard or via API and Webhooks. Use the data to build your own rules, automate workflows, and make informed decisions.
Pricing
Simple, transparent pricing for every stage of growth.
Free
$0one time 1,000 requests
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For Traffic quality visibility
Includes:
- Visitor identification
- Anonymous detection
- Traffic & Visitor Risk Scoring
- Device Intelligence
- IP & Location Intelligence
- OS & Network Intelligence
- Mismatch detection
- Real-time dashboard
- Standard support
- API access
- Webhooks
Starter
$99/ month25,000 requests
$3.96 per 1,000 requests
Designed for ongoing traffic monitoring and paid acquisition validation.
Includes:
- Visitor identification
- Anonymous detection
- Traffic & Visitor Risk Scoring
- Device Intelligence
- IP & Location Intelligence
- OS & Network Intelligence
- Mismatch detection
- Real-time dashboard
- Standard support
- API access
- Webhooks
Growth
Most Popular$399/ month150,000 requests
$2.66 per 1,000 requests
For abuse detection and automated control. Move from monitoring to coordinated risk detection.
Everything in Starter +
- Cross-entity correlation
- Ready-made abuse patterns
- Pattern-based identity risk scoring
- Data export
- 99.9% SLA
- Priority support
Scale
$999/ month500,000 requests
$1.99 per 1,000 requests
For high-volume infrastructure. Optimized for high-traffic and regulated platforms.
Everything in Growth +
- Lower cost per 1,000 requests
Compare all features
Full breakdown of capabilities across plans
Frequently asked questions
- What is ShieldLabs?
- ShieldLabs is a traffic quality and risk intelligence service. The platform evaluates visit quality, assigns an explainable Risk Score, and detects abuse patterns. ShieldLabs helps companies identify anonymous users and manage traffic risks.
- What is ShieldLabs used for?
- ShieldLabs is used to assess traffic quality and identify anonymous visitors, as well as to detect multi-accounting, trial abuse, giveaway abuse, bonus program abuse, and other scenarios where it is important to understand visit risk level and prevent abuse.
- How does ShieldLabs work?
- ShieldLabs collects signals from the device, operating system, browser, network, and connection type. The system correlates these signals across layers and over time to detect masking techniques, linked identities, and abuse patterns. Each visit and overall traffic receive a clear Risk Score with explainable reasons.
- What can ShieldLabs detect?
- ShieldLabs can detect the use of VPN, proxy and TOR, anti-detect browsers, server and data center infrastructure, multi-accounting and other masking techniques.
- Who is ShieldLabs for?
- ShieldLabs is suitable for companies operating in industries such as Banking and Fintech, SaaS and internet platforms, e-commerce and retail, gambling and iGaming, Web3 and crypto, travel and hospitality, video gaming, media and streaming, as well as technology platforms and marketplaces.
- What is Risk Score?
- Risk Score is a numerical assessment of the overall risk level of a specific visit. It is formed based on a combination of factors: network characteristics, anonymity indicators, environment inconsistencies, and signal repetition. A high Score indicates an increased probability of an anonymous visit.
- How is Risk Score calculated?
- Each detected risk signal contributes to the final score. These may include connection masking indicators, use of server or suspicious infrastructure, environment parameter inconsistencies, and repetition of signals over time. Risk Score reflects the cumulative risk level and explains each signal.
- How is ShieldLabs different from traditional abuse prevention systems and traffic risk assessment platforms?
- ShieldLabs focuses on deep traffic quality and anonymity level analysis at the device, operating system, browser, and network levels. The system detects masking indicators and related accounts, provides an explainable Risk Score, and ready-made abuse patterns. Unlike classic enterprise platforms, ShieldLabs delivers enterprise-level analytics without the need to overpay for complex and expensive tools.
- Does ShieldLabs automatically block users?
- No. ShieldLabs provides Risk Score and detailed risk signals. The blocking decision is made by you.
- How accurate is ShieldLabs?
- ShieldLabs accurately detects anonymity indicators and environment inconsistencies even when IP changes or masking tools are used. Actual accuracy depends on the use case and selected risk thresholds.
- Can ShieldLabs be bypassed?
- ShieldLabs detects connection masking indicators and environment inconsistencies. Even when IP or account changes, the system can identify recurring risk signals.
- Does ShieldLabs affect real users?
- No. The system operates in the background and does not require additional actions from visitors.
- Can a visitor be recognized when IP changes?
- Yes. ShieldLabs generates a persistent visit identifier based on environment parameters, allowing recognition of repeated visits even when IP or network changes.
- Does ShieldLabs provide API and Webhooks?
- Yes. ShieldLabs provides API and Webhooks to receive Risk Score and detailed data.
- How long does integration take?
- Integration takes a few minutes. After connection, the system immediately begins analyzing visits.
Understanding traffic quality means less abuse and less revenue loss
We'll help you ship a clean integration and keep false positives low.